Association Rule Mining to Extract Knowledge from Online Store Transactions of a Turkish Retail Company: A Case Study

Year 2014, Volume: 4 Issue: 4, 861 - 865, 01.12.2014

Elif Şafak Sivri Mustafa Cem Kasapbaşı Fettullah Karabiber

Abstract

Data mining techniques have been implemented in many fields namely, marketing, insurance, finance, medicine, computer science and many more. In marketing it is used as a tool to cluster and classify customers so that their buying patterns, demographical information, market basket can be analyzed to help the CRM representative and decision makers [1]. In this study online store transactions of multi-branch Turkish Retail Company have been analyzed and many associations rules have been discovered. The analyzed volume of transactions of completed sales exceeds 14000 for a single season. At first data is cleaned from unrelated fields then presented to R studio to implement the Apriori algorithm[2] in order to extract knowledge and obtain association rules between goods. Results are proven be worthy over the conventional methodologies. The extracted data are tested successfully with a sample group of customers to validate the association rules which give unique insights about customer behaviors.

Keywords

Association analysis, Apriori Analysis, Data Mining

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